The present invention relates to physiological monitoring instruments and, in particular, monitors and sensors that include mechanisms for indicating a quality of detected signals and accuracy or confidence level of physiological measurements estimated from the signals.
Typically, for physiological monitoring instruments that include a monitor and a patient sensor, the monitor is unable to accurately determine a quality of a signal obtained from the sensor. The invention will be explained by reference to a preferred embodiment concerning pulse oximeter monitors and pulse oximetry sensors, but it should be realized the invention is applicable to any generalized patient monitor and associated patient sensor. The invention provides a way of more accurately determining a quality of a signal detected by a sensor; a way of determining a relative accuracy of a physiological characteristic derived or calculated from the signal; and a way of delineating a transition boundary between a normal signal for the sensor being used in its normal application, and a signal considered to be abnormal for the sensor being used, to allow a monitor to determine if the sensor is being misapplied.
Pulse oximetry is typically used to measure various blood flow characteristics including, but not limited to, the blood oxygen saturation of hemoglobin in arterial blood and the heartbeat of a patient. Measurement of these characteristics has been accomplished by the use of a non-invasive sensor that passes light through a portion of a patient's blood perfused tissue and photo-electrically senses the absorption and scattering of light in such tissue. The amount of light absorbed and scattered is then used to estimate the amount of blood constituent in the tissue using various algorithms known in the art. The “pulse” in pulse oximetry comes from the time varying amount of arterial blood in the tissue during a cardiac cycle. The signal processed from the sensed optical signal is a familiar plethysmographic waveform due to the cycling light attenuation.
The light passed through the tissue is typically selected to be of two or more wavelengths that are absorbed by the blood in an amount related to the amount of blood constituent present in the blood. The amount of transmitted light that passes through the tissue varies in accordance with the changing amount of blood constituent in the tissue and the related light absorption.
To estimate arterial blood oxygen saturation of a patient, conventional two-wavelength pulse oximeters emit light from two light emitting diodes (LEDs) into a pulsatile tissue bed and collect the transmitted light with a photodiode (or photo-detector) positioned on an opposite surface (i.e., for transmission pulse oximetry) or an adjacent surface (i.e., for reflectance pulse oximetry). The LEDs and photo-detector are typically housed in a reusable or disposable oximeter sensor that couples to a pulse oximeter electronics and display unit. One of the two LEDs' primary wavelength is selected at a point in the electromagnetic spectrum where the absorption of oxyhemoglobin (HbO2) differs from the absorption of reduced hemoglobin (Hb). The second of the two LEDs' wavelength is selected at a different point in the spectrum where the absorption of Hb and HbO2 differs from those at the first wavelength. Commercial pulse oximeters typically utilize one wavelength in the near red part of the visible spectrum near 660 nanometers (nm) and one in the near infrared (IR) part of the spectrum in the range of 880-940 nm.
Oxygen saturation can be estimated using various techniques. In one common technique, first and second photo-current signals generated by the photo-detector from red and infrared light are conditioned and processed to determine AC and DC signal components and a modulation ratio of the red to infrared signals. This modulation ratio has been observed to correlate well to arterial oxygen saturation. Pulse oximeters and sensors are empirically calibrated by measuring the modulation ratio over a range of in vivo measured arterial oxygen saturations (SaO2) on a set of patients, healthy volunteers, or animals. The observed correlation is used in an inverse manner to estimate blood oxygen saturation (SpO2) based on the measured value of modulation ratios. The estimation of oxygen saturation using modulation ratio is described in U.S. Pat. No. 5,853,364, entitled “METHOD AND APPARATUS FOR ESTIMATING PHYSIOLOGICAL PARAMETERS USING MODEL-BASED ADAPTIVE FILTERING”, issued Dec. 29, 1998, and U.S. Pat. No. 4,911,167, entitled “METHOD AND APPARATUS FOR DETECTING OPTICAL PULSES”, issued Mar. 27, 1990. The relationship between oxygen saturation and modulation ratio is further described in U.S. Pat. No. 5,645,059, entitled “MEDICAL SENSOR WITH MODULATED ENCODING SCHEME,” issued Jul. 8, 1997. All three patents are assigned to the assignee of the present invention and incorporated herein by reference.
The accuracy of the estimates of the blood flow characteristics depends on a number of factors. For example, the light absorption characteristics typically vary from patient to patient depending on their physiology. Moreover, the absorption characteristics vary depending on the location (e.g., the foot, finger, ear, and so on) where the sensor is applied. Further, the light absorption characteristics vary depending on the design or model of the sensor. Also, the light absorption characteristics of any single sensor design vary from sensor to sensor (e.g., due to different characteristics of the light sources or photo-detector, or both). The clinician applying the sensor correctly or incorrectly may also have a large impact in the results, for example, by loosely or firmly applying the sensor or by applying the sensor to a body part which is inappropriate for the particular sensor design being used.
Some oximeters “qualify” measurements before displaying them on the monitor. One conventional technique processes (i.e., filters) the measured plethysmographic waveform and performs tests to detect and reject measurements perceived corrupted and inaccurate. Since oximeters are typically designed to be used with a wide variety of sensors having widely differing performance characteristics, the monitor signal “qualification” algorithms are necessarily crude, and often result in only superficial indications of signal quality, signal reliability, and ultimately a confidence level in a patient physiological characteristic estimated or calculated from the signal. In many instances, the monitor simply discards data associated with low quality signals, but otherwise gives no indication to a healthcare giver as to whether any physiological characteristic displayed on a monitor is highly reliable or not. Hence, the signal quality measurements obtained from such crude algorithms are relatively poor and convey little useful information to a caregiver.